H. Sasaki and N. Kubota (Japan)
Map Building, Monitoring, Sensor Networks, Computational Intelligence, Image Processing
An environmental model is very important to understand what occurs in natute. This paper discusses how to gather environmental information based on map building by networked robots and monitoring by sensor networks. First, we explain how to apply a steady-state genetic algorithm for self-localization and map building for illuminance measurement of a mobile robot. The map is represented by 2 dimensional discrete cell space. According to the measured distance by laser range finder, the map is updated sequentially. When the difference between the measured distance and the map data is large, a steady-state genetic algorithm corrects the self-location. Next, we explain the image processing methods for monitoring of targets in the envriomenment. Finally we show several experimental results of the proposed method.
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